In order to provide high-quality services to customers, internet service providers perform capacity planning to ensure that they can adequately service the demands placed on their systems and provide responses to requests in sufficiently fast time.
As information technology (IT) and application infrastructures become more complex, predicting and controlling system performance and capacity planning have become a difficult task to many organizations. For larger IT projects, it is not uncommon for the cost factors related to performance tuning, performance management, and capacity planning to result in the largest and least controlled expense. Furthermore, application performance issues have an immediate impact on customer satisfaction. A sudden slowdown of an enterprise-wide application can affect a large population of customers, can lead to delayed projects, and ultimately can result in company financial loss.
Traditional capacity planning techniques are often inadequate for accurately predicting resource needs. In many cases, the workload actually encountered by a deployed system does not correspond with a synthetic workload that was expected for the system. Further, workloads often include composite transactions (i.e., a single transaction comprising a plurality of transactions), and determining a resource cost for such composite transactions is challenging for system designers.